public class RegSymFuzzyGP extends GeneticIndividualForSymbRegr
fuzzy system of symbolic regression
m, X, Xfuzzy, Y, Yfuzzy, Yo
CUSTOM_CESAR, fitnessType, g, STANDARD
Constructor and Description |
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RegSymFuzzyGP(double kmin,
double kmax,
int ne,
int typectes,
int NCTES,
int MAXH,
int tf,
Randomize r)
Constructor.
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RegSymFuzzyGP(RegSymFuzzyGP p)
Constructor.
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Modifier and Type | Method and Description |
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GeneticIndividual |
clone()
This method clone a fuzzy system of symbolic regession
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void |
crossover(GeneticIndividual p2,
GeneticIndividual p3,
GeneticIndividual p4,
int IDCRUCE)
This method implement the cross operation.
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void |
debug()
This method is for debug
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GeneticIndividual |
FuzzyGPRegresionSimbolicaClona()
This method generate a genetic individual from a fuzzy system of symbolic regession
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double[] |
getConsts()
This methods return a copy of the constant part
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boolean[] |
getUsedConsts()
This method returns information about used constant
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void |
localOptimization(int MAXITER,
int idoptimization)
This method calculates a local optimization
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void |
mutation(double alpha,
int IDMUTA)
This method implement the mutation operation
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void |
parametersFromGenotype()
This method obtain the parameters of a genetic individual from the genotype
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void |
Random()
This method generate a random genotype and obtain the parameters from another one
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void |
set(RegSymFuzzyGP p)
This method assing the properties of a fuzzy system of symbolic regession to another one
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void |
setConsts(double[] ctes)
This method modifies constant part for this individual with parameter passed
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asignaejemplos, debug_fitness, fitness, getYo, MSE
public RegSymFuzzyGP(double kmin, double kmax, int ne, int typectes, int NCTES, int MAXH, int tf, Randomize r)
Constructor. Generate a new fuzzy system of symbolic regression
kmin
- Minimum kkmax
- Maximum kne
- Number of inputstypectes
- Type of constantNCTES
- Number of constantMAXH
- Maximum heighttf
- Type of fitnessr
- Randompublic RegSymFuzzyGP(RegSymFuzzyGP p)
Constructor. Generate a new fuzzy system of symbolic regession from another one
p
- The fuzzy system of symbolic regessionpublic GeneticIndividual clone()
This method clone a fuzzy system of symbolic regession
clone
in class GeneticIndividual
public void set(RegSymFuzzyGP p)
This method assing the properties of a fuzzy system of symbolic regession to another one
p
- The fuzzy system of symbolic regessionpublic GeneticIndividual FuzzyGPRegresionSimbolicaClona()
This method generate a genetic individual from a fuzzy system of symbolic regession
public void parametersFromGenotype()
This method obtain the parameters of a genetic individual from the genotype
parametersFromGenotype
in class GeneticIndividual
public void Random()
This method generate a random genotype and obtain the parameters from another one
Random
in class GeneticIndividual
public void mutation(double alpha, int IDMUTA) throws invalidMutation
This method implement the mutation operation
mutation
in class GeneticIndividual
alpha
- Index mutationIDMUTA
- Type of mutationinvalidMutation
- message if errorpublic void crossover(GeneticIndividual p2, GeneticIndividual p3, GeneticIndividual p4, int IDCRUCE) throws invalidCrossover
This method implement the cross operation. The cross generates two objects of class 'individuogen'
crossover
in class GeneticIndividual
p2
- Genetic individualp3
- Genetic individualp4
- Genetic individualIDCRUCE
- Type of crossinvalidCrossover
- Message if errorpublic void debug()
This method is for debug
debug
in class GeneticIndividualForSymbRegr
public void setConsts(double[] ctes)
This method modifies constant part for this individual with parameter passed
ctes
- The constantpublic double[] getConsts()
This methods return a copy of the constant part
public boolean[] getUsedConsts()
public void localOptimization(int MAXITER, int idoptimization) throws invalidOptim
This method calculates a local optimization
localOptimization
in class GeneticIndividual
MAXITER
- Maximum iterationsidoptimization
- Type of optimizationinvalidOptim
- Message if error